GRPN Stock Forecast: A Hold For The Next 16 Weeks

Outlook: Groupon Inc. Common Stock is assigned short-term B2 & long-term B2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Hold
Time series to forecast n: for Weeks²
Methodology : Transductive Learning (ML)
Hypothesis Testing : Wilcoxon Rank-Sum Test
Surveillance : Major exchange and OTC

¹The accuracy of the model is being monitored on a regular basis.(15-minute period)

²Time series is updated based on short-term trends.

Summary

Groupon Inc. Common Stock prediction model is evaluated with Transductive Learning (ML) and Wilcoxon Rank-Sum Test^1,2,3,4 and it is concluded that the GRPN stock is predictable in the short/long term. Transductive learning is a supervised machine learning (ML) method in which the model is trained on both labeled and unlabeled data. The goal of transductive learning is to predict the labels of the unlabeled data. Transductive learning is a hybrid of inductive and semi-supervised learning. Inductive learning algorithms are trained on labeled data only, while semi-supervised learning algorithms are trained on a combination of labeled and unlabeled data. Transductive learning algorithms can achieve better performance than inductive learning algorithms on tasks where there is a small amount of labeled data. This is because transductive learning algorithms can use the unlabeled data to help them learn the relationships between the features and the labels. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold

Key Points

1. What statistical methods are used to analyze data?
2. Is now good time to invest?
3. Stock Forecast Based On a Predictive Algorithm

GRPN Target Price Prediction Modeling Methodology

We consider Groupon Inc. Common Stock Decision Process with Transductive Learning (ML) where A is the set of discrete actions of GRPN stock holders, F is the set of discrete states, P : S × F × S → R is the transition probability distribution, R : S × F → R is the reaction function, and γ ∈ [0, 1] is a move factor for expectation.^1,2,3,4

F(Wilcoxon Rank-Sum Test)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Transductive Learning (ML)) X S(n):→ 16 Weeks $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of GRPN stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Transductive Learning (ML)

Transductive learning is a supervised machine learning (ML) method in which the model is trained on both labeled and unlabeled data. The goal of transductive learning is to predict the labels of the unlabeled data. Transductive learning is a hybrid of inductive and semi-supervised learning. Inductive learning algorithms are trained on labeled data only, while semi-supervised learning algorithms are trained on a combination of labeled and unlabeled data. Transductive learning algorithms can achieve better performance than inductive learning algorithms on tasks where there is a small amount of labeled data. This is because transductive learning algorithms can use the unlabeled data to help them learn the relationships between the features and the labels.

Wilcoxon Rank-Sum Test

The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a non-parametric test that is used to compare the medians of two independent samples. It is a rank-based test, which means that it does not assume that the data is normally distributed. The Wilcoxon rank-sum test is calculated by first ranking the data from both samples, and then finding the sum of the ranks for one of the samples. The Wilcoxon rank-sum test statistic is then calculated by subtracting the sum of the ranks for one sample from the sum of the ranks for the other sample. The p-value for the Wilcoxon rank-sum test is calculated using a table of critical values. The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that the null hypothesis is true.

 

For further technical information as per how our model work we invite you to visit the article below: 

How do AC Investment Research machine learning (predictive) algorithms actually work?

GRPN Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: GRPN Groupon Inc. Common Stock
Time series to forecast: 16 Weeks

According to price forecasts, the dominant strategy among neural network is: Hold

Strategic Interaction Table Legend:

X axis: *Likelihood% (The higher the percentage value, the more likely the event will occur.)

Y axis: *Potential Impact% (The higher the percentage value, the more likely the price will deviate.)

Z axis (Grey to Black): *Technical Analysis%

Financial Data Adjustments for Transductive Learning (ML) based GRPN Stock Prediction Model

1. There are two types of components of nominal amounts that can be designated as the hedged item in a hedging relationship: a component that is a proportion of an entire item or a layer component. The type of component changes the accounting outcome. An entity shall designate the component for accounting purposes consistently with its risk management objective.
2. For the purpose of applying paragraph 6.5.11, at the point when an entity amends the description of a hedged item as required in paragraph 6.9.1(b), the amount accumulated in the cash flow hedge reserve shall be deemed to be based on the alternative benchmark rate on which the hedged future cash flows are determined.
3. A hedge of a firm commitment (for example, a hedge of the change in fuel price relating to an unrecognised contractual commitment by an electric utility to purchase fuel at a fixed price) is a hedge of an exposure to a change in fair value. Accordingly, such a hedge is a fair value hedge. However, in accordance with paragraph 6.5.4, a hedge of the foreign currency risk of a firm commitment could alternatively be accounted for as a cash flow hedge.
4. Compared to a business model whose objective is to hold financial assets to collect contractual cash flows, this business model will typically involve greater frequency and value of sales. This is because selling financial assets is integral to achieving the business model's objective instead of being only incidental to it. However, there is no threshold for the frequency or value of sales that must occur in this business model because both collecting contractual cash flows and selling financial assets are integral to achieving its objective.

*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.

GRPN Groupon Inc. Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B2	B2
Income Statement	Baa2	Baa2
Balance Sheet	Caa2	C
Leverage Ratios	C	B2
Cash Flow	Ba1	C
Rates of Return and Profitability	Caa2	C

*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?

Conclusions

Groupon Inc. Common Stock is assigned short-term B2 & long-term B2 estimated rating. Groupon Inc. Common Stock prediction model is evaluated with Transductive Learning (ML) and Wilcoxon Rank-Sum Test^1,2,3,4 and it is concluded that the GRPN stock is predictable in the short/long term. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold

Prediction Confidence Score

Trust metric by Neural Network: 78 out of 100 with 845 signals.

References

1. Wager S, Athey S. 2017. Estimation and inference of heterogeneous treatment effects using random forests. J. Am. Stat. Assoc. 113:1228–42
2. Arjovsky M, Bottou L. 2017. Towards principled methods for training generative adversarial networks. arXiv:1701.04862 [stat.ML]
3. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Tesla Stock: Hold for Now, But Watch for Opportunities. AC Investment Research Journal, 220(44).
4. M. J. Hausknecht and P. Stone. Deep recurrent Q-learning for partially observable MDPs. CoRR, abs/1507.06527, 2015
5. Dudik M, Langford J, Li L. 2011. Doubly robust policy evaluation and learning. In Proceedings of the 28th International Conference on Machine Learning, pp. 1097–104. La Jolla, CA: Int. Mach. Learn. Soc.
6. Chen X. 2007. Large sample sieve estimation of semi-nonparametric models. In Handbook of Econometrics, Vol. 6B, ed. JJ Heckman, EE Learner, pp. 5549–632. Amsterdam: Elsevier
7. C. Wu and Y. Lin. Minimizing risk models in Markov decision processes with policies depending on target values. Journal of Mathematical Analysis and Applications, 231(1):47–67, 1999

Frequently Asked Questions

Q: What is the prediction methodology for GRPN stock?
A: GRPN stock prediction methodology: We evaluate the prediction models Transductive Learning (ML) and Wilcoxon Rank-Sum Test
Q: Is GRPN stock a buy or sell?
A: The dominant strategy among neural network is to Hold GRPN Stock.
Q: Is Groupon Inc. Common Stock stock a good investment?
A: The consensus rating for Groupon Inc. Common Stock is Hold and is assigned short-term B2 & long-term B2 estimated rating.
Q: What is the consensus rating of GRPN stock?
A: The consensus rating for GRPN is Hold.
Q: What is the prediction period for GRPN stock?
A: The prediction period for GRPN is 16 Weeks

People also ask

⚐ What are the top stocks to invest in right now?
☵ What happens to stocks when they're delisted?